insects

Communication

Monitoring Exotic Beetles with Inexpensive Attractants:A Case Study

Enrico Ruzzier 1,2,* , Andrea Galli 3 and Luciano Bani 2,3

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Citation: Ruzzier, E.; Galli, A.; Bani,

L. Monitoring Exotic Beetles with

Inexpensive Attractants: A Case

Study. Insects 2021, 12, 462. https://

doi.org/10.3390/insects12050462

Academic Editor: Tibor Magura

Received: 1 May 2021

Accepted: 14 May 2021

Published: 17 May 2021

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1 Department of Agronomy, Food, Natural Resources, Animals and the Environment (DAFNAE),University of Padova, Viale dell’Universita 16, Legnaro, 35020 Padova, Italy

2 World Biodiversity Association Onlus c/o NAT LAB Forte Inglese, Portoferraio, 57037 Livorno, Italy;luciano.bani@unimib.it

3 Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1,20126 Milano, Italy; a.galli57@campus.unimib.it

* Correspondence: enrico.ruzzier@unipd.it

Simple Summary: Detecting and monitoring exotic and invasive beetles is a complex activity, andmultiple species still manage to evade controls. Citizen science can be an important adjunct in alienspecies monitoring programs, but to have a greater chance of success, it must employ traps andattractants that are easy to gather and use. Bottle traps baited with food products are successfullyused during long term faunistic surveys, and the same methodology can be adapted to alien speciesdetection and monitoring. In this article, we tested the use of bottles baited with apple cider vinegar,red wine, and 80% ethyl alcohol in capturing exotic and invasive beetles in the surroundings ofMalpensa Airport (Italy). The traps proved effective, and in the traps with vinegar as an attractant,they captured four out of five invasive Nitidulidae, as well as the only invasive Scarabaeidae presentin the area. Popillia japonica’s response to apple cider vinegar is documented for the first time andsuggests the use of this attractant in monitoring surveys for this species, especially if supported bycitizen science programs. The substantial reduction in the activity time of the traps seems to haveconsiderably reduced collateral catches of native fauna.

Abstract: Detecting and monitoring exotic and invasive Coleoptera is a complex activity to imple-ment, and citizen science projects can provide significant contributions to such plans. Bottle traps aresuccessfully used in wildlife surveys and can also be adapted for monitoring alien species; however,a sustainable, large scale trapping plan must take into account the collateral catches of native speciesand thus minimize its impact on local fauna. In the present paper, we tested the use of bottles baitedwith standard food products that can be purchased in every supermarket and immediately used(apple cider vinegar, red wine, and 80% ethyl alcohol) in capturing exotic and invasive beetles inthe area surrounding Malpensa Airport (Italy). In particular, we reduced the exposition type of thetraps in each sampling round to three days in order to minimize native species collecting. We founda significant effect of the environmental covariates (trap placement, temperature, humidity, andforest type) in affecting the efficiency in catching target beetles. Nearly all invasive Nitidulidae andScarabaeidae known to be present in the area were captured in the traps, with apple cider vinegarusually being the most effective attractant, especially for the invasive Popillia japonica.

Keywords: alien species; biodiversity; Coleoptera; Nitidulidae; Popillia; vinegar

1. Introduction

Among European countries, Italy has the most exotic taxa (species that are not nativeto a specific ecosystem), several of which are invasive (organisms that cause ecological oreconomic harm in an ecosystem where they are not native) [1]; among these, Coleopteraalone account for more than 300 intercepted or established species [2–13]. Insect introduc-tions through human-mediated dispersal is ever increasing because of globalization, and

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represents a serious threat to biodiversity, local economies and animal and plant health [14].The ever-increasing number and types of goods transported and the speed at which com-mercial traffic occurs, associated with the opening of new trade routes, are increasinglyresulting in faunal exchanges among and within biogeographic realms [15]. Italy’s pre-disposition to beetle (Coleoptera) introductions is likely associated with its geographicposition in the center of the Mediterranean, being at the crossroads of much commerce toand from Europe [1,16].

Attention and awareness towards alien species have increased in recent decades, eventhough strategies to reduce future invasions have not yet been implemented in an effectiveand widespread manner on a global scale [17].

If we consider the number of exotic species recorded in the last few years, and espe-cially those collected fortuitously, it is clear that current monitoring strategies are ineffectiveat detecting several beetle families. It is for this reason that great effort has been investedin improving monitoring strategies, survey methods, and traps [18,19], with a focus onthe main entry points such as seaports and airports (i.e., [20,21]). However, much of theserecent developments have targeted primarily families of forest insects, mostly wood borers,such as Curculionidae: Scolytinae and Platypodinae, Cerambycidae, and Buprestidae(e.g., [22–24]). Furthermore, biosecurity surveillance suffers from two major issues, namely:(1) effective monitoring strategies, especially those that target multiple taxa, which aregenerally expensive because of the cost of traps and pheromones, and (2) difficulty inapplying targeted monitoring strategies simultaneously and on a national scale.

For this reason, the scientific community is increasingly availing itself of the support ofcitizen science as a means of strengthening its surveillance capacity (e.g., [25,26]). However,for a monitoring plan supported by citizen science to be effective, it is necessary that it iseasily reproducible, low-cost, and does not involve a heavy workload for volunteers.

Bottle traps is a methodology commonly and successfully used in faunistic sur-veys [27,28]. Bottle traps are inexpensive, easy to make and transport, and have beenrecently suggested and applied in bark and ambrosia beetle (Scolytinae and Platypodinae)monitoring through citizen participation [29–31].

Based on these concepts, we decided to conduct a trial intended to evaluate if bottletraps could be used to monitor certain exotic beetles that are not commonly targeted withstandard traps (e.g., Lindgren funnels traps and cross-vane panel traps) and pheromones,especially using food products as lures that can be purchased directly at the supermarket.In the scientific literature, there are many attractive mixtures made from fermented goods(such as honey, bananas, and beer; e.g., [32,33]). However, as we could not expect allvolunteers to produce such attractive mixtures, we opted for three affordable products thatcan be used directly as they are when purchased, namely: food-grade ethyl alcohol (whichwill be referred to as alcohol), red wine, and apple cider vinegar.

However, as the objective of this trial was to target exotic species, the exposure timesof our traps were reduced to only three days each during each survey round. This decisionstarted from the assumption that invasive species are characterized by biological andecological traits that make them more prone to rapidly respond to generic olfactory stimuli(e.g., food/reproduction sources) compared with native species. Given the collateral catchthat these monitoring activities can have on native species, we expected that reducing thetraps’ exposure time would maintain the capture of exotics, while minimizing the impacton native species.

In the present study, we evaluated (1) the effectiveness of bottle traps baited withnon-fermented goods and short exposure times in catching exotic beetles, (2) the beetlefamilies and species collected in terms of diversity and abundance, and (3) how the differentbaits varied in attractiveness to target beetle species. Furthermore, we tried to assess theeffect of temperature, humidity, environmental surroundings, and trap placement ontrapping efficiency.

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2. Materials and Methods2.1. Study Area

The study area is centered on the Malpensa International Airport (MXP), the largestinternational airport in northern Italy, located in the Ferno Municipality (Varese Province),within the Lombardy Regional Park of Ticino Valley, about 50 km northwest of Milan.The airport grounds are largely surrounded by deciduous and mixed (broad-leaved andconiferous) forests and urban areas, and, to a lesser extent, agricultural areas and shrubland(Figure 1). Among the trees, the dominant taxa are oaks (Quercus spp.), maples (Acer spp.),and Scots pine (Pinus sylvestris). Most of the woodlands are managed as coppice, and thepresence of exotic trees is not negligible, with the Locust tree (Robinia pseudoacacia) amongthe most widespread species.

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2. Materials and Methods 2.1. Study Area

The study area is centered on the Malpensa International Airport (MXP), the largest international airport in northern Italy, located in the Ferno Municipality (Varese Prov-ince), within the Lombardy Regional Park of Ticino Valley, about 50 km northwest of Mi-lan. The airport grounds are largely surrounded by deciduous and mixed (broad-leaved and coniferous) forests and urban areas, and, to a lesser extent, agricultural areas and shrubland (Figure 1). Among the trees, the dominant taxa are oaks (Quercus spp.), maples (Acer spp.), and Scots pine (Pinus sylvestris). Most of the woodlands are managed as cop-pice, and the presence of exotic trees is not negligible, with the Locust tree (Robinia pseu-doacacia) among the most widespread species.

Figure 1. Study area. Map illustrating land use classes and the sampling localities in the surround-ing of the Malpensa International Airport, MXP (Ferno and Somma Lombardo municipalities, Varese Province, Italy); numbers indicate the 13 sampling sites where the trial was performed.

2.2. Experimental Design, Traps, and Baits The traps were placed in 13 sampling sites identified to account for habitat covariates,

i.e., the forest type (broadleaved vs. mixed) and forest edge vs. forest interior condition (interior: condition with forest fractional cover >90% evaluated in a buffer of 250 m around trapping site), based on DUSAF digital cartography [34] (Table 1). In each sampling site, three traps were used, each baited with either 80% food alcohol, commercial red wine (11.5% alcohol), and apple cider vinegar (4% acetic acid), for a total of 39 traps. No

Figure 1. Study area. Map illustrating land use classes and the sampling localities in the surroundingof the Malpensa International Airport, MXP (Ferno and Somma Lombardo municipalities, VareseProvince, Italy); numbers indicate the 13 sampling sites where the trial was performed.

2.2. Experimental Design, Traps, and Baits

The traps were placed in 13 sampling sites identified to account for habitat covariates,i.e., the forest type (broadleaved vs. mixed) and forest edge vs. forest interior condition(interior: condition with forest fractional cover >90% evaluated in a buffer of 250 m aroundtrapping site), based on DUSAF digital cartography [34] (Table 1). In each sampling site,three traps were used, each baited with either 80% food alcohol, commercial red wine (11.5%alcohol), and apple cider vinegar (4% acetic acid), for a total of 39 traps. No preservatives

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were added. In each sampling site, the three traps were placed along the perimeter of anideal circle with about a 15 m radius (thus having a distance of at least 30 m among traps) toavoid their mutual influence on capture events; all traps were placed 2.5 m from the ground.Each trap was built using a 500 mL volume PET (polyethylene terephthalate). A 5 × 8.5 cmwindow was created on half of each bottle by removing a sizeable lateral portion, leavingthe rest of the bottle intact (to guarantee the structural integrity and support of the modestweight of the bait). Each set of baited traps was left in action for 72 h, and then removed andemptied each week between 31 July and 29 September 2020, for a total of seven trappingperiods. For each trapping session, we recorded the absolute minimum and maximumtemperature during the three days of activity of the traps, the three-days mean of themean daily temperatures, and the three-days mean of the humidity degree. As the threetemperature values were correlated within each trapping session, we used the absolutemaximum temperature (Table 2). The meteorological data were obtained from the airportmeteorological station.

Table 1. Location of the sampling sites in which the group of three traps was triggered with different baits. The forest coversin a buffer of 250 m around the sampling site used to define the forest conditions (interior condition: forest cover >90%) andforest type.

Site Number Nord (WGS84/UTMZone 32N)

East (WGS84/UTMZone 32N)

Forest Cover(250-m Buffer) Forest Condition Forest Type

1 5,053,409 476,170 98% interior broadleaved2 5,055,451 476,779 100% interior mixed3 5,057,292 477,621 58% edge broadleaved4 5,056,847 478,549 52% edge mixed5 5,055,783 478,335 87% edge mixed6 5,052,549 480,498 79% edge broadleaved7 5,052,204 480,113 88% edge broadleaved8 5,053,714 480,070 76% edge mixed9 5,054,249 480,724 99% interior mixed

10 5,050,105 478,906 82% edge broadleaved11 5,049,577 478,796 100% interior broadleaved12 5,056,516 479,151 100% interior mixed13 5,054,071 479,998 99% interior mixed

Table 2. Meteorological data obtained from the airport station for each of the three-days trapping sessions.

SessionNumber Placement Date Control Date Abs. Min. Temp. (◦C)

3-Day SessionAbs. Max. Temp. (◦C)

3-Day SessionMean Temp. (◦C)

3-Day SessionMean Humidity3-Days

Session

1 31 July 2020 3 August 2020 18 36 26.3 64.02 7 August 2020 10 August 2020 17 34 26.5 58.03 14 August 2020 17 August 2020 18 32 24.5 68.04 28 August 2020 31 August 2020 13 27 21.0 77.05 4 September 2020 7 September 2020 14 29 20.8 73.06 11 September 2020 14 September 2020 17 31 23.3 70.57 25 September 2020 28 September 2020 4 21 13.0 64.3

All of the non-Coleoptera (i.e., Diptera, Lepidoptera, Hymenoptera, and Hemiptera)collected during the survey were not considered in the analyses and were discarded.

2.3. Analyses

We evaluated the overall effectiveness of each type of bait (red wine, vinegar, or alco-hol), considering the overall number of individuals of exotic species pooled together caughtby each kind of bait in each site and session, accounting for both habitat and meteorologicalcovariates. The same model was applied to the overall number of individuals for thenative species subset. The analysis was performed using a negative binomial regressionfor modelling count data using MASS package [35] in R version 4.0.3 [36]. The assessmentof the data distribution for the dependent variable was performed using the fitdistrplus

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package [37]. Plots of the conditional effects (habitat variables) and main effect (meteorolog-ical variables) of covariates were made using the sjPlot package [38], whose functionalitydepends on the ggplot2 package [39]. The same analysis was then performed to evaluate thespecific overall effectiveness of each bait, considering the number of individuals pertainingto the most commonly trapped species.

3. Results

During the two-months survey period (i.e., seven three-day sessions), in the 13 sam-pling sites, we caught a total of 531 individuals (437 pertaining to exotic and 94 to nativespecies). The 14 species of beetles collected belonged to Scolytinae, Nitidulidae, andScarabaeidae (Figure 2 and Table 3). Among the species collected, five are consideredinvasive in Europe (Carpophilus lugubris, Epuraea luteola, Epuraea ocularis, Glischrochilusquadrisignatus, and Popilia japonica; Figure 3).

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assessment of the data distribution for the dependent variable was performed using the fitdistrplus package [37]. Plots of the conditional effects (habitat variables) and main effect (meteorological variables) of covariates were made using the sjPlot package [38], whose functionality depends on the ggplot2 package [39]. The same analysis was then performed to evaluate the specific overall effectiveness of each bait, considering the number of indi-viduals pertaining to the most commonly trapped species.

3. Results During the two-months survey period (i.e., seven three-day sessions), in the 13 sam-

pling sites, we caught a total of 531 individuals (437 pertaining to exotic and 94 to native species). The 14 species of beetles collected belonged to Scolytinae, Nitidulidae, and Scar-abaeidae (Figure 2 and Table 3). Among the species collected, five are considered invasive in Europe (Carpophilus lugubris, Epuraea luteola, Epuraea ocularis, Glischrochilus quadrisigna-tus, and Popilia japonica; Figure 3).

Figure 2. Beetle families collected during the survey; total number of individuals given in brackets.

Table 3. Coleoptera species collected during the survey. (V—Vinegar; W—wine; E—Alcohol.)

Species Family/Subfamily Origin Status Attractant N° of

Individuals Carpophilus lugubris Murray 1864 Nitidulidae Nearctic Invasive V(3); W(2) 5

Cryptarcha strigata (Fabricius, 1787) Nitidulidae W-Palaearctic Native W(1) 1 Epuraea guttata (Olivier, 1811) Nitidulidae W-Palaearctic Native V(6); W(1) 7

Epuraea luteola (Erichson, 1843) Nitidulidae E-Palaearctic Invasive V(5) 5 Epuraea ocularis (Fairmaire, 1849) Nitidulidae E-Palaearctic Invasive V(176); W(28); E(1) 205

Epuraea unicolor (Olivier, 1790) Nitidulidae Palaearctic Native V(5) 5 Glischrochilus quadrisignatus (Say, 1835) Nitidulidae Nearctic Invasive V(3); W(1) 4

Soronia grisea (Linnaeus, 1758) Nitidulidae Palaearctic Native V(2); W(9) 11 Anisandrus dispar Fabricius, 1792 Scolytinae Palaearctic Native E(4) 4

Xyleborinus saxesenii (Ratzeburg, 1837) Scolytinae Palaearctic Native W(1) E581) 59 Cetonia aurata (Linnaeus, 1758) Scarabaeidae W-Palaearctic Native W(1) 1

Popillia japonica (Newman, 1838) Scarabaeidae E-Palaearctic Invasive V(161); W(51); E(6) 218 Potosia cuprea (Fabricius, 1775) Scarabaeidae W-Palaearctic Native W(1) 1 Protaetia speciosa (Adams, 1817) Scarabaeidae W-Palaearctic Native W(1) 5

The most common species caught were P. japonica (Scarabaeidae: Rutelinae), with 212 individuals (40% of the overall individual caught and 49% of the individuals of exotic

Figure 2. Beetle families collected during the survey; total number of individuals given in brackets.

Table 3. Coleoptera species collected during the survey. (V—Vinegar; W—wine; E—Alcohol.)

Species Family/Subfamily Origin Status Attractant N◦ ofIndividuals

Carpophilus lugubris Murray 1864 Nitidulidae Nearctic Invasive V(3); W(2) 5Cryptarcha strigata (Fabricius, 1787) Nitidulidae W-Palaearctic Native W(1) 1

Epuraea guttata (Olivier, 1811) Nitidulidae W-Palaearctic Native V(6); W(1) 7Epuraea luteola (Erichson, 1843) Nitidulidae E-Palaearctic Invasive V(5) 5

Epuraea ocularis (Fairmaire, 1849) Nitidulidae E-Palaearctic Invasive V(176); W(28); E(1) 205Epuraea unicolor (Olivier, 1790) Nitidulidae Palaearctic Native V(5) 5

Glischrochilus quadrisignatus (Say, 1835) Nitidulidae Nearctic Invasive V(3); W(1) 4Soronia grisea (Linnaeus, 1758) Nitidulidae Palaearctic Native V(2); W(9) 11

Anisandrus dispar Fabricius, 1792 Scolytinae Palaearctic Native E(4) 4Xyleborinus saxesenii (Ratzeburg, 1837) Scolytinae Palaearctic Native W(1) E(581) 59

Cetonia aurata (Linnaeus, 1758) Scarabaeidae W-Palaearctic Native W(1) 1Popillia japonica (Newman, 1838) Scarabaeidae E-Palaearctic Invasive V(161); W(51); E(6) 218Potosia cuprea (Fabricius, 1775) Scarabaeidae W-Palaearctic Native W(1) 1Protaetia speciosa (Adams, 1817) Scarabaeidae W-Palaearctic Native W(1) 5

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species), and E. ocularis (Nitidulidae), with 159 individuals (30% of the overall individual caught and 36% of the exotic species). The third most common species was the native X. saxesenii (Scolytinae), with 58 individuals (11% of the overall individual caught and 62% of native species).

The negative binomial regression models used to assess each bait’s effectiveness in attracting the overall number of exotic and native species explained 40% and 13% of the sample deviance, respectively. For the exotic species subset, the model identified the type of bait, the absolute maximum temperature, and the mean humidity as statistically signif-icant for affecting the overall number of individuals caught in each of the three traps per site and session (Table 4). The conditional effect of each covariate is depicted in Figure 3.

(a)

(b)

Figure 3. Exotic species: effect of the covariates of the negative binomial regression model affect-ing the number of individuals caught by each of the three traps per site and per session; (a) condi-tional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

Table 4. Exotic species. Effectiveness of baits in attracting individuals of all species pooled to-gether, accounting for the effects of habitat and meteorological covariates considered in the nega-tive binomial regression model.

Covariates Estimate SE of Estimate z-Value p

Figure 3. Exotic species: effect of the covariates of the negative binomial regression model affectingthe number of individuals caught by each of the three traps per site and per session; (a) conditionaleffect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior);(b) main effect of meteorological covariates.

The most common species caught were P. japonica (Scarabaeidae: Rutelinae), with212 individuals (40% of the overall individual caught and 49% of the individuals of exoticspecies), and E. ocularis (Nitidulidae), with 159 individuals (30% of the overall individualcaught and 36% of the exotic species). The third most common species was the native X.saxesenii (Scolytinae), with 58 individuals (11% of the overall individual caught and 62% ofnative species).

The negative binomial regression models used to assess each bait’s effectiveness inattracting the overall number of exotic and native species explained 40% and 13% of thesample deviance, respectively. For the exotic species subset, the model identified the type ofbait, the absolute maximum temperature, and the mean humidity as statistically significantfor affecting the overall number of individuals caught in each of the three traps per siteand session (Table 4). The conditional effect of each covariate is depicted in Figure 3.

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Table 4. Exotic species. Effectiveness of baits in attracting individuals of all species pooled together,accounting for the effects of habitat and meteorological covariates considered in the negative binomialregression model.

Covariates Estimate SE of Estimate z-Value p

(intercept) −1.657 2.998 −0.553 0.581Bait: vinegar 4.311 0.584 7.379 <0.001

Bait: wine 2.705 0.594 4.552 <0.001Forest type: mixed forests 0.201 0.367 0.549 0.583

Forest cover condition: interior −0.579 0.371 −1.559 0.119Absolute maximum temperature 0.127 0.044 2.901 0.004

Mean humidity −0.075 0.033 −2.296 0.022

The same model applied to the native species subset identified the type of bait and themean humidity as statistically significant (Table 5). The conditional effect of each covariateis depicted in Figure 4.

Table 5. Native species. Effectiveness of baits in attracting individuals of all species pooled together,accounting for the effects of habitat and meteorological covariates considered in the negative binomialregression model.

Covariates Estimate SE of Estimate z-Value p

(intercept) −6.772 3.344 −2.025 0.042Bait: vinegar −1. 187 0.479 −2.479 0.013

Bait: wine −0.986 0.467 −2.110 0.035Forest type: mixed forests 0.345 0.403 0.857 0.391

Forest cover condition: interior −0.411 0.406 −1.012 0.312Absolute maximum temperature 0.039 0.050 0.786 0.431

Mean humidity 0.073 0.036 2.038 0.042

For the three most common trapped species (two exotic and one native), the modelsfor the P. japonica, E. oculari, and X. saxesenii explained 72%, 40%, and 32% of the sampledeviance, respectively. We must highlight that all of the individuals, but one of X. saxesenii,were caught in alcohol. Thus, to find the covariate that affects the number of individualscaught, we used only those collected by the traps triggered by alcohol.

For P. japonica, the type of bait’s effectiveness differed significantly, and both thehabitat and meteorological covariates significantly affected the number of individualscaught. Specifically, both vinegar and wine positively enhanced the trap efficiency incollecting P. japonica, with vinegar being more effective than wine. Furthermore, thenumber of collected specimens increased with increasing temperatures and captures, andwere substantially higher when traps were placed at the edges of broadleaved forests(Table 6). The conditional effect of each covariate is depicted in Figure 5.

Table 6. Popillia japonica. Effectiveness of baits in attracting individuals of the species, account-ing for the effects of habitat and meteorological covariates considered in the negative binomialregression model.

Covariates Estimate SE of Estimate z-Value p

(intercept) −9.751 9.453 −1.032 0.302Bait: vinegar 3.136 0.922 3.401 0.001

Bait: wine 2.047 0.940 2.178 0.029Forest type: mixed forests −1.827 0.680 −2.685 0.007

Forest cover condition: interior −2.574 0.795 −3.237 0.001Absolute maximum temperature 0.519 0.172 3.012 0.003

Mean humidity −0.147 0.078 −1.893 0.058

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Covariates Estimate SE of Estimate z-Value p (intercept) −1.657 2.998 −0.553 0.581

Bait: vinegar 4.311 0.584 7.379 <0.001 Bait: wine 2.705 0.594 4.552 <0.001

Forest type: mixed forests 0.201 0.367 0.549 0.583 Forest cover condition: interior −0.579 0.371 −1.559 0.119

Absolute maximum temperature 0.127 0.044 2.901 0.004 Mean humidity −0.075 0.033 −2.296 0.022

The same model applied to the native species subset identified the type of bait and the mean humidity as statistically significant (Table 5). The conditional effect of each co-variate is depicted in Figure 4.

(a)

(b)

Figure 4. Native species: effect of the covariates of the negative binomial regression model affect-ing the number of individuals caught by each of the three traps per site and per session; (a) condi-tional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

Table 5. Native species. Effectiveness of baits in attracting individuals of all species pooled to-gether, accounting for the effects of habitat and meteorological covariates considered in the nega-tive binomial regression model.

Figure 4. Native species: effect of the covariates of the negative binomial regression model affectingthe number of individuals caught by each of the three traps per site and per session; (a) conditionaleffect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior);(b) main effect of meteorological covariates.

For E. ocularis, the type of bait also significantly influenced the effectiveness of trapping,but only the habitat covariates showed a substantial effect on the number of individualscaught, and particularly the forest type. For this species, vinegar and wine positivelyenhanced the trap efficiency, with vinegar also being more efficient than wine in this case;in addition, mixed forest enhanced the traps’ efficiency (Table 7). The conditional effect ofeach covariate is depicted in Figure 6.

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Covariates Estimate SE of Estimate z-Value p (intercept) −6.772 3.344 −2.025 0.042

Bait: vinegar −1. 187 0.479 −2.479 0.013 Bait: wine −0.986 0.467 −2.110 0.035

Forest type: mixed forests 0.345 0.403 0.857 0.391 Forest cover condition: interior −0.411 0.406 −1.012 0.312

Absolute maximum temperature 0.039 0.050 0.786 0.431 Mean humidity 0.073 0.036 2.038 0.042

For the three most common trapped species (two exotic and one native), the models for the P. japonica, E. oculari, and X. saxesenii explained 72%, 40%, and 32% of the sample deviance, respectively. We must highlight that all of the individuals, but one of X. saxese-nii, were caught in alcohol. Thus, to find the covariate that affects the number of individ-uals caught, we used only those collected by the traps triggered by alcohol.

For P. japonica, the type of bait’s effectiveness differed significantly, and both the hab-itat and meteorological covariates significantly affected the number of individuals caught. Specifically, both vinegar and wine positively enhanced the trap efficiency in collecting P. japonica, with vinegar being more effective than wine. Furthermore, the number of col-lected specimens increased with increasing temperatures and captures, and were substan-tially higher when traps were placed at the edges of broadleaved forests (Table 6). The conditional effect of each covariate is depicted in Figure 5.

Table 6. Popillia japonica. Effectiveness of baits in attracting individuals of the species, accounting for the effects of habitat and meteorological covariates considered in the negative binomial regres-sion model.

Covariates Estimate SE of Estimate z-Value p (intercept) −9.751 9.453 −1.032 0.302

Bait: vinegar 3.136 0.922 3.401 0.001 Bait: wine 2.047 0.940 2.178 0.029

Forest type: mixed forests −1.827 0.680 −2.685 0.007 Forest cover condition: interior −2.574 0.795 −3.237 0.001

Absolute maximum temperature 0.519 0.172 3.012 0.003 Mean humidity −0.147 0.078 −1.893 0.058

(a) (b)

Figure 5. Popillia japonica: effect of the covariates of the negative binomial regression model affecting the number of indi-viduals caught by each of the three traps per site and per session; (a) conditional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

For E. ocularis, the type of bait also significantly influenced the effectiveness of trap-ping, but only the habitat covariates showed a substantial effect on the number of

Figure 5. Popillia japonica: effect of the covariates of the negative binomial regression model affecting the number ofindividuals caught by each of the three traps per site and per session; (a) conditional effect of habitat covariates (forest type:broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

Table 7. Epuraea ocularis. Effectiveness of baits in attracting individuals of the species, account-ing for the effects of habitat and meteorological covariates considered in the negative binomialregression model.

Covariates Estimate SE of Estimate z-Value p

(intercept) −8.111 3.705 −2.189 0.029Bait: vinegar 5.382 1.115 4.829 <0.001

Bait: wine 3.410 1.129 3.019 0.003Forest type: mixed forests 1.083 0.466 2.327 0.020

Forest cover condition: interior −0.392 0.461 −0.851 0.395Absolute maximum temperature −0.016 0.052 −0.311 0.756

Mean humidity 0.051 0.040 1.292 0.196

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individuals caught, and particularly the forest type. For this species, vinegar and wine positively enhanced the trap efficiency, with vinegar also being more efficient than wine in this case; in addition, mixed forest enhanced the traps’ efficiency (Table 7). The condi-tional effect of each covariate is depicted in Figure 6.

For X. saxesenii, only the bait type was significant in determining the number of indi-viduals caught in the traps Table 8. The conditional effect of covariates is depicted in Fig-ure 7.

Table 7. Epuraea ocularis. Effectiveness of baits in attracting individuals of the species, accounting for the effects of habitat and meteorological covariates considered in the negative binomial regres-sion model.

Covariates Estimate SE of Estimate z-Value p (intercept) −8.111 3.705 −2.189 0.029

Bait: vinegar 5.382 1.115 4.829 <0.001 Bait: wine 3.410 1.129 3.019 0.003

Forest type: mixed forests 1.083 0.466 2.327 0.020 Forest cover condition: interior −0.392 0.461 −0.851 0.395

Absolute maximum temperature −0.016 0.052 −0.311 0.756 Mean humidity 0.051 0.040 1.292 0.196

(a) (b)

Figure 6. Epuraea ocularis: effect of the covariates of the negative binomial regression model affecting the number of indi-viduals caught by each of the three traps per site and per session; (a) conditional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

Table 8. Xyleborinus saxesenii. Effectiveness of alcohol in attracting individuals of the species, ac-counting for the effects of habitat and meteorological covariates considered in the negative bino-mial regression model.

Covariates Estimate SE of Estimate z-Value p (intercept) −64.815 45.690 −1.419 0.156

Forest type: mixed forests 1.544 0.860 1.796 0.073 Forest cover condition: interior −0.972 0.861 −1.129 0.259

Absolute maximum temperature 0.711 0.596 1.194 0.233 Mean humidity 0.597 0.390 1.530 0.126

Figure 6. Epuraea ocularis: effect of the covariates of the negative binomial regression model affecting the number ofindividuals caught by each of the three traps per site and per session; (a) conditional effect of habitat covariates (forest type:broadleaved vs. mixed; forest condition: edge vs. interior); (b) main effect of meteorological covariates.

For X. saxesenii, only the bait type was significant in determining the number ofindividuals caught in the traps Table 8. The conditional effect of covariates is depicted inFigure 7.

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Table 8. Xyleborinus saxesenii. Effectiveness of alcohol in attracting individuals of the species,accounting for the effects of habitat and meteorological covariates considered in the negative binomialregression model.

Covariates Estimate SE of Estimate z-Value p

(intercept) −64.815 45.690 −1.419 0.156Forest type: mixed forests 1.544 0.860 1.796 0.073

Forest cover condition: interior −0.972 0.861 −1.129 0.259Absolute maximum temperature 0.711 0.596 1.194 0.233

Mean humidity 0.597 0.390 1.530 0.126

Insects 2021, 12, x FOR PEER REVIEW 10 of 14

Figure 7. Xyleborinus saxesenii: effect of the negative binomial regression model’s covariates affect-ing the number of individuals caught by the trap triggered with alcohol per site and session. Only the conditional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs. interior) is shown, as neither of the two meteorological variables showed significant ef-fects.

4. Discussion The survey allowed for the collection of thirteen different species among Scolytinae,

Nitidulidae, and Scarabaeidae. It is striking that no other beetle family responded posi-tively to the attractants, suggesting that neither the type of traps nor the attractants were adequate; it is also plausible that the sampling season was too late compared with most of the species’ phenology. If we exclude Scolytinae, represented by two native species which were almost exclusively collected with alcohol baited traps, both Nitidulidae and Scarabaeidae were included as invasive species. Four out of the eight species of Nitiduli-dae belong to invasive taxa, representing the 90% of the total number of the nitidulid spec-imens. Carpophilus lugubris is one of the ten Carpophilus species indicated as invasive in Italy [40]; however, it most probably is the only species present in the area, given its recent introduction and expansion throughout Veneto and Friuli Venezia Giulia [41,42]. Epuraea luteola and Epuraea guttata are two of the three invasive Epuraea occurring in Italy, but the only occur in Lombardy, as the third species is limited to southern Italy [40]. Glischrochilus quadrisignatus is the only invasive species of the genus in Italy [40]. Stelidota geminata (Say, 1825), the only other invasive nitidulid present in Lombardy [43], was not recorded in our survey. Popillia japonica is the only invasive Scarabaeidae in Italy [16]; this species alone constituted about 97% of the scarabaeoid specimens.

The fact that this simple trial was able to detect almost, if not all, of the exotic Nitid-ulidae and Scarabaeidae present in the area suggests, at least for these two families, how home-made traps baited with food products, using apple cider vinegar in particular, may be effective at detecting exotic and invasive beetles, and could be an important addition to monitoring plans around entry points. Long standing food-baited traps are very effec-tive in catching beetles and, in several cases, they have to be modified in order not to kill rare and threatened species (e.g., [44,45]). The proportion of exotic compared with native species collected in our trial suggests that minimizing the activity period of the traps does not substantially affect the traps’ capacity in catching non-native species. Trapping effi-ciency against exotic species seems to be substantially affected by trap placement (margin vs. interior of forest), absolute maximum temperature, and mean humidity; however, this result may be substantially biased by the two overrepresented E. ocularis and P. japonica. A similar effect may be caused by X. saxesenii on the native species pool. As expected,

Figure 7. Xyleborinus saxesenii: effect of the negative binomial regression model’s covariates affectingthe number of individuals caught by the trap triggered with alcohol per site and session. Only theconditional effect of habitat covariates (forest type: broadleaved vs. mixed; forest condition: edge vs.interior) is shown, as neither of the two meteorological variables showed significant effects.

4. Discussion

The survey allowed for the collection of thirteen different species among Scolytinae,Nitidulidae, and Scarabaeidae. It is striking that no other beetle family responded positivelyto the attractants, suggesting that neither the type of traps nor the attractants were adequate;it is also plausible that the sampling season was too late compared with most of the species’phenology. If we exclude Scolytinae, represented by two native species which were almostexclusively collected with alcohol baited traps, both Nitidulidae and Scarabaeidae wereincluded as invasive species. Four out of the eight species of Nitidulidae belong to invasivetaxa, representing the 90% of the total number of the nitidulid specimens. Carpophiluslugubris is one of the ten Carpophilus species indicated as invasive in Italy [40]; however,it most probably is the only species present in the area, given its recent introduction andexpansion throughout Veneto and Friuli Venezia Giulia [41,42]. Epuraea luteola and Epuraeaguttata are two of the three invasive Epuraea occurring in Italy, but the only occur inLombardy, as the third species is limited to southern Italy [40]. Glischrochilus quadrisignatusis the only invasive species of the genus in Italy [40]. Stelidota geminata (Say, 1825), the onlyother invasive nitidulid present in Lombardy [43], was not recorded in our survey. Popilliajaponica is the only invasive Scarabaeidae in Italy [16]; this species alone constituted about97% of the scarabaeoid specimens.

The fact that this simple trial was able to detect almost, if not all, of the exotic Nitidul-idae and Scarabaeidae present in the area suggests, at least for these two families, how

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home-made traps baited with food products, using apple cider vinegar in particular, maybe effective at detecting exotic and invasive beetles, and could be an important addition tomonitoring plans around entry points. Long standing food-baited traps are very effective incatching beetles and, in several cases, they have to be modified in order not to kill rare andthreatened species (e.g., [44,45]). The proportion of exotic compared with native speciescollected in our trial suggests that minimizing the activity period of the traps does notsubstantially affect the traps’ capacity in catching non-native species. Trapping efficiencyagainst exotic species seems to be substantially affected by trap placement (margin vs.interior of forest), absolute maximum temperature, and mean humidity; however, thisresult may be substantially biased by the two overrepresented E. ocularis and P. japonica.A similar effect may be caused by X. saxesenii on the native species pool. As expected,Scolytinae was the only group responding systematically to alcohol traps, and the fact thatthe native X. saxesenii constituted almost all of the individuals collected is perfectly in linewith the tendencies of this species to respond to a wide range of ethanol concentrations [46].Furthermore, the efficiency when catching X. saxesenii is not affected by the environmentalcovariates, and is most probably attributable to the species dispersal capabilities, longphenology, and polyphagy.

Nitidulidae is a group of primary interest, given the number of exotic and invasivespecies introduced in Europe [40]. The effectiveness of vinegar traps in rapidly detectingexotic sap beetles may serve as an important tool in monitoring new introductions or thespread of newly acclimatized species. Fermented baits are commonly used to investigateNitidulidae [47,48]; the capability of E. luteola, E. ocularis, C. lugubris, and G. quadrisignatusto rapidly respond to wine and vinegar seems promising in using bottle traps for theircapture; furthermore, given the similar ecological niche that these have with most of theothers invasive species, we may expect a similar attraction efficiency by both attractants.In addition to direct damage to crops, Nitidulidae can be vectors of important pathogenicfungi such as Ophiostomatales [49] and Microascales [50]; consequently, their early detec-tion may have a relevant role as phytosanitary security. The substantial effect given by theforest type in the capture efficiency of E. ocularis is probably attributable to its generalisthabits and polyphagy, with adults able to feed on rotten fruit, flowers, sapping trees, andlarvae developing in the fruit body of tree-fungi or decaying organic matter [40,51].

Popillia japonica is a highly polyphagous invasive pest outside its native range, so farlimited to Lombardy and Piedmont in Italy [52]. Because of the substantial damage it isable to cause, as well as its excellent dispersal capacity, this species is currently controlledthrough mass trapping, with traps commonly baited with chemical attractants such asfood-type volatile and sex pheromones [53–55]. The capture of this species with both wineand vinegar traps was unexpected and constituted an absolute novelty, as it is the firstresponse of P. japonica towards these two attractants, vinegar in particular. ScarabaeidaeRutelinae are rarely collected with fruit/fermented and baited traps in the Palearctic [56,57],while they constitute a substantial fraction of the tropics’ trapped biomass [58]. However,a particular sensitivity of P. japonica towards volatile compounds released during fruitripening or rotting can be deduced from Hammons et al. [59,60], where the species havebeen repeatedly documented as feeding on grapes in the USA. Concerning environmentalcovariates, the trapping efficiency against P. japonica is substantially affected by forest type,forest cover condition, and absolute maximum temperature. Forest composition and trapplacement (forest edge/interior) have a significant effect, as P. japonica prefers ecotones,areas hosting the greater variety of feeding plants, and where the species move by flying.Furthermore, ecotonal areas may present grass patches suitable for egg deposition andlarval development [61]. The positive effect of high temperatures in increasing trappingefficiency is defined by a general increase of P. japonica activity combined with a greaterattractant volatility [62].

Vinegar efficiency against Nitidulidae and P. japonica in heterogeneous habitats sug-gests a good effectiveness of the traps in agricultural and peri-urban environments, aswell as other anthropized entry points such as airports and ports. Furthermore, adopting

Insects 2021, 12, 462 12 of 15

short trapping sections repeated over time seems to not affect native beetles through anunnecessary over-trapping.

5. Conclusions

The traps used in this study can be produced in a short time, using recycled or easilyavailable materials. Furthermore, as the traps are light and compact, they can be comfort-ably managed by one person, even in large numbers. The attractants are readily availableat a low cost, making this survey technique very useful in citizen science projects forlarge-scale monitoring projects. Apple cider vinegar has proven to be the most affordableand still the most efficient bait, capable of attracting exotic and invasive beetles in almost allconditions; wine has intermediate attractivity and may be used as a coadjutant of vinegar;conversely, in our context, high-grade alcohol targets exclusively native Scolytinae. Aswhat has been presented here is only a first trial, it will certainly be interesting to replicatethe monitoring using different types of vinegar or wine and to evaluate the influence ofother potential co-factors, including seasonality. It would be interesting to identify and testnew types of inexpensive attractants for other families of beetles other than those used inthis study.

As citizen science data are not usually collected following a sampling design typicalof standardized monitoring programs, we stress that the collection of environmentalvariables, beside the collection of the specimens, is crucial for a correct interpretation ofthe records. Specifically, the position of the traps is essential information that must beprovided by citizens involved in monitoring activities, along with the baits used and thetime of exposure of the traps. In particular, if these monitoring projects are directed againstinvasive species, citizen scientists should keep in mind that the time exposure of baitedtraps should be minimized in order to reduce the impact on native fauna.

Given the strong attractivity of vinegar against P. japonica, it is plausible that themassive trapping of this species through a supervised citizen science action may becomea substantial contribution and integration to the control strategies developed by localphytosanitary institutions, especially in cultivated and suburban areas.

Author Contributions: Conceptualization, E.R. and L.B.; methodology, E.R. and A.G.; formal analy-sis, L.B.; investigation, A.G.; data curation, E.R., A.G., and L.B.; writing—original draft preparation,E.R. and L.B.; writing—review and editing, E.R., A.G., and L.B. All authors have read and agreed tothe published version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board Statement: Not applicable.

Data Availability Statement: The original dataset is available under request.

Acknowledgments: The authors thanks Robert Haack (USDA), Gareth Powell (Brigham YoungUniversity), Massimo Faccoli (Università degli Studi di Padova), and Jorge Ari Noriega (Universidadde los Andes) for providing valuable comments and recommendations that improved the quality ofthis manuscript.

Conflicts of Interest: The authors declare no conflict of interest.

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